svcR: a package for Support Vector Clustering improved with Geometric Hashing. Application to Lexical Pattern Discovery

We developed an R toolkit to manage data described by attributes, able to make clusters with a support vector clustering method (SVC). We have implemented an original 2D-grid labeling approach to extract clusters to optimize time processing. In this sense, svc can be seen as an efficient cluster extraction if clusters are separable in a 2-D map. Secondly we showed that this SVC approach using a Jaccard-Radial base kernel can help to classify well enough a set of terms into ontological classes and help to define regular expression rules for information extraction in documents; our case study concerns a set of terms and documents about developmental and molecular biology.